Abstract
Land cover type is an important signature that is usually used to understand the interaction between the ground surfaces with the local temperature. Various land cover types such as high density built up areas, vegetation, bare land and water bodies are areas where heat signature are measured using remote sensing image. The aim of this study is to analyse the impact of land surface temperature on land cover types. The objectives are 1) to analyse the mean temperature for each land cover types and 2) to analyse the relationship of temperature variation within land cover types: built up area, green area, forest, water bodies and bare land. The method used in this research was supervised classification for land cover map and mono window algorithm for land surface temperature (LST) extraction. The statistical analysis of post hoc Tukey test was used on an image captured on five available images. A pixel-based change detection was applied to the temperature and land cover images. The result of post hoc Tukey test for the images showed that these land cover types: built up-green, built up-forest, built up-water bodies have caused significant difference in the temperature variation. However, built up-bare land did not show significant impact at p<0.05. These findings show that green areas appears to have a lower temperature difference, which is between 2° to 3° Celsius compared to urban areas. The findings also show that the average temperature and the built up percentage has a moderate correlation with R<sup>2</sup> = 0.53. The environmental implications of these interactions can provide some insights for future land use planning in the region.
Highlights
It is essential to incorporate remote sensed data in the study of urban climate to obtain synoptic view required to understand the interaction between natural processes and human modification of those processes (Stefanov & Brazel, 2007)
This opinion was supported by Stathoupoulou and Cartalis (2007) who further highlighted that different construction materials reduce turbulent heat transfer and long wave radiative heat loss due to street canyon geometry
This study was aimed at exploring remote sensing data product for each pixel to produce predictions of how the temperature interacts with land cover types in the local setting
Summary
It is essential to incorporate remote sensed data in the study of urban climate to obtain synoptic view required to understand the interaction between natural processes and human modification of those processes (Stefanov & Brazel, 2007). The canyon geometry, air pollution, buildings and construction materials were hypothesised by Oke (1982) as the causes of UHI due to urbanisation and energy balance changes This opinion was supported by Stathoupoulou and Cartalis (2007) who further highlighted that different construction materials reduce turbulent heat transfer and long wave radiative heat loss due to street canyon geometry. They reduce latent heat loss by evaporation due to the replacement of natural green surfaces with dry surfaces and increase anthropogenic heat emissions into the urban atmosphere. It is important to mitigate anthropogenic heat emission as one of the pillars of UHI countermeasures as recognised by the Inter-Ministry Coordination Committee (2004)
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